.png){kind=icon}
.png){kind=icon}
Return
Robust intelligent tracking control with PID-type learning algorithm
.png){kind=icon}
PRE
AI
DOI：10.1016/j.neucom.2007.01.002.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper proposes a robust intelligent tracking controller (RITC) for a class of unknown nonlinear systems. The proposed RITC system is comprised of a neural controller and a robust controller. The neural controller is designed to approximate an ideal controller using a proportional-integral-derivative (PID)-type learning algorithm in the sense of Lyapunov function, and the robust controller is designed to achieve L-2 tracking performance with desired attenuation level. Finally, to investigate the effectiveness of the RITC system, the proposed design methodology is applied to control two chaotic dynamical systems. The simulation results verify that the proposed RITC system using PID-type learning algorithm can achieve faster convergence of the tracking error and controller parameters than that using I-type learning algorithm. (c) 2007 Elsevier B.V. All rights reserved.
Keywords:
adaptive control
neural network control
robust control
Lyapunov function
chaotic dynamic system
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6.5
Papers:
2.5W
Citations:
6.5W
Organization
No organization information available